code: def _create_fake_samples():
      """Creates a fake set of samples.
  
      Returns:
        Tuple with fake images, class labels and latent values.
      """
      rs = np.random.RandomState(0)
      images = rs.randint(256, size=(NUM_IMAGES, 64, 64)).astype(
          "uint8"
      )
  
      classes = []
      values = []
      for num_factors, factor_values in zip(
          FACTOR_COUNTS, FACTOR_VALUES
      ):
          classes.append(
              rs.randint(num_factors, size=(NUM_IMAGES), dtype=np.int64)
          )
          values.append(rs.choice(factor_values, size=(NUM_IMAGES)))
  
      return images, classes.T, values.T
  
file_path: datasets/tensorflow_datasets/testing/fake_data_generation/dsprites.py
imports: import os
  from absl import app
  from absl import flags
  import h5py
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.testing import test_utils
label_desc: Use image node_id 1 for calling a global function with example usage: _create_fake_samples() and returns: images,  classes,  values